A cluster Monte Carlo algorithm with a conserved order parameter

Abstract

We propose a cluster simulation algorithm for statistical ensembles with fixed order parameter. We use the tethered ensemble, which features Helmholtz's effective potential rather than Gibbs's free energy, and in which canonical averages are recovered with arbitrary accuracy. For the D = 2,3 Ising model our method's critical slowing down is comparable to that of canonical cluster algorithms. Yet, we can do more than merely reproduce canonical values. As an example, we obtain a competitive value for the 3D Ising anomalous dimension from the maxima of the effective potential.

4 pages, 2 color figures. Minor improvements and update of table 3

References in corpus (7)

• Microcanonical Approach to the Simulation of First-Order Phase Transitions
• Monte Carlo study of the evaporation/condensation transition on different Ising lattices
• Cluster simulations of loop models on two-dimensional lattices
• Dynamic critical behavior of the Chayes-Machta-Swendsen-Wang algorithm
• Critical speeding-up in a local dynamics for the random-cluster model
• Tethered Monte Carlo: computing the effective potential without critical slowing down
• Weak first order transition in the three-dimensional site-diluted Ising antiferromagnet in a magnetic field